Inefficient workflows in hospitals are a growing problem as the demand for medical services increases faster than an institution's ability to assist patient needs. To support the population's medical demand, h...
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When e-mail users wish to manage4 their e-mails, they need to read the e-mail content to identify the e-mail properties, and then classify and manage the e-mails themselves. However, large numbers of e-mails become ve...
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Due to the strong turbulence that exists in the business environment, the view is sometimes articulated that the time horizon of decisions is no longer a hallmark of strategic management. Opposing views argue that a t...
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ISBN:
(纸本)9781917204101
Due to the strong turbulence that exists in the business environment, the view is sometimes articulated that the time horizon of decisions is no longer a hallmark of strategic management. Opposing views argue that a turbulent environment changes the trajectory of reaching future objectives determined by strategic decisions. Such trajectories require the company to be agile, which is manifested by seizing opportunities. Opportunities arise because the environment is volatile. An example of market opportunity is the unsatisfied demand for products. Buyers are driven by different motives when choosing between products that are alternative to them. From the producer's point of view, the purchase is therefore random. As a consequence, the alignment of the offered product portfolio with the actual purchasing decisions of customers is undetermined. In this article, we address the problem of determining the product portfolio structure expected by customers, i.e. one that is consistent with their future purchasing decisions. We hypothesise that this problem can be represented by a model of flows between alternative resources. Problems of this type are solved using Markov Chain Monte Carlo (MCMC) methods. In order to discover the expected demand (opportunity), we simulated the flow model we developed using the Metropolis-Hastings algorithm, which is a special case of the MCMC method used in AI. Due to operating on numerical data, such simulations fall under quantitative research. In the article, we present a model of customer flows between alternative products and then the simulation result, which is the expected value of these flows (stationary point). We convert this value into the structure of the product portfolio using a model of customer purchasing decisions that we have developed. The obtained results confirm the effectiveness of our method and have significant practical value, especially for SMEs. It also enables the assessment of the company's product strategy based
Encouraging citizens to invest in small-scale renewable resources is crucial for transitioning towards a sustainable and clean energy *** energy communities(LECs)are expected to play a vital role in this ***,energy sc...
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Encouraging citizens to invest in small-scale renewable resources is crucial for transitioning towards a sustainable and clean energy *** energy communities(LECs)are expected to play a vital role in this ***,energy scheduling in LECs presents various challenges,including the preservation of customer privacy,adherence to distribution network constraints,and the management of computational *** paper introduces a novel approach for energy scheduling in renewable-based LECs using a decentralized optimization *** proposed approach uses the Limitedmemory Broyden–Fletcher–Goldfarb–Shanno(L-BFGS)method,significantly reducing the computational effort required for solving the mixed integer programming(MIP)*** incorporates network constraints,evaluates energy losses,and enables community participants to provide ancillary services like a regulation reserve to the grid *** assess its robustness and efficiency,the proposed approach is tested on an 84-bus radial distribution *** indicate that the proposed distributed approach not only matches the accuracy of the corresponding centralized model but also exhibits scalability and preserves participant privacy.
The distributed flexible job shop scheduling problem(DFJSP)has attracted great attention with the growth of the global manufacturing *** DFJSP research only considers machine constraints and ignores worker *** one cri...
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The distributed flexible job shop scheduling problem(DFJSP)has attracted great attention with the growth of the global manufacturing *** DFJSP research only considers machine constraints and ignores worker *** one critical factor of production,effective utilization of worker resources can increase ***,energy consumption is a growing concern due to the increasingly serious environmental ***,the distributed flexible job shop scheduling problem with dual resource constraints(DFJSP-DRC)for minimizing makespan and total energy consumption is studied in this *** solve the problem,we present a multi-objective mathematical model for DFJSP-DRC and propose a Q-learning-based multi-objective grey wolf optimizer(Q-MOGWO).In Q-MOGWO,high-quality initial solutions are generated by a hybrid initialization strategy,and an improved active decoding strategy is designed to obtain the scheduling *** further enhance the local search capability and expand the solution space,two wolf predation strategies and three critical factory neighborhood structures based on Q-learning are *** strategies and structures enable Q-MOGWO to explore the solution space more efficiently and thus find better Pareto *** effectiveness of Q-MOGWO in addressing DFJSP-DRC is verified through comparison with four algorithms using 45 *** results reveal that Q-MOGWO outperforms comparison algorithms in terms of solution quality.
Humanitarian aid distribution often prioritizes rapid relief operations or emergency services under time constraints, as opposed to commercial transportation problems, where the primary objective is to minimize operat...
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Machine-to-machine (M2M) communication plays a fundamental role in autonomous IoT (Internet of Things)-based infrastructure, a vital part of the fourth industrial revolution. Machine-type communication devices(MTCDs) ...
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Machine-to-machine (M2M) communication plays a fundamental role in autonomous IoT (Internet of Things)-based infrastructure, a vital part of the fourth industrial revolution. Machine-type communication devices(MTCDs) regularly share extensive data without human intervention while making all types of decisions. Thesedecisions may involve controlling sensitive ventilation systems maintaining uniform temperature, live heartbeatmonitoring, and several different alert systems. Many of these devices simultaneously share data to form anautomated system. The data shared between machine-type communication devices (MTCDs) is prone to risk dueto limited computational power, internal memory, and energy capacity. Therefore, securing the data and devicesbecomes challenging due to factors such as dynamic operational environments, remoteness, harsh conditions,and areas where human physical access is difficult. One of the crucial parts of securing MTCDs and data isauthentication, where each devicemust be verified before data transmission. SeveralM2Mauthentication schemeshave been proposed in the literature, however, the literature lacks a comprehensive overview of current M2Mauthentication techniques and the challenges associated with them. To utilize a suitable authentication schemefor specific scenarios, it is important to understand the challenges associated with it. Therefore, this article fillsthis gap by reviewing the state-of-the-art research on authentication schemes in MTCDs specifically concerningapplication categories, security provisions, and performance efficiency.
The implementation of carbon capture and storage in the petrochemical industry is one of the means of *** research focuses on a comprehensive technical analysis of the deployment of post-combustion carbon capture and ...
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The implementation of carbon capture and storage in the petrochemical industry is one of the means of *** research focuses on a comprehensive technical analysis of the deployment of post-combustion carbon capture and storage based on monoethanolamine absorption in the petrochemical *** olefin complex petrochemical industry in Tuban,Indonesia,is the basis for the analysis,which includes a steam cracker,polyethylene,polypropylene,and raw pyrolysis gasoline hydrotreating units,with capacities of 1000,940,600,and 570 kilotons/year,*** total energy consumption is about 16024.53 GJ/h,and the CO_(2) emissions are about 1.6 megatons/*** on these plant systems,comprehensive technical analyses of the implementation of carbon capture and storage in that industry were performed using Aspen HYSYS®simulation *** analysis was carried out to determine the total CO_(2) captured,energy intensity,monoethanolamine consumption,and net CO_(2) captured in various scenarios based on the number of absorber column stages,absorption pressure,and desorption *** CO_(2) storage site is about 100 km away and is transported by an onshore pipeline with a supercritical phase of CO_(2).The optimal net CO_(2) capture value is achieved by setting up a 50-stage absorber column with a pressure of 1 barg and a temperature of 110℃ at the top of the desorber column,resulting in a CO_(2) capture yield of 86.4%and an energy intensity of 12.6 GJ/ton CO_(2).Under these conditions,the net CO_(2) captured in the scenario based on gas power plants’electricity is 0.225 megatons/year,while in the scenario based on gas power plants incorporating 30%biomass electricity,it is 0.544 megatons/*** increased use of renewable energy in carbon capture and storage facilities,more net CO_(2) is *** study can be applied to various cases of post-combustion carbon capture and storage implementation in the industrial sector,especially in the
Parcel hub (PH), as one of the logistic system entities, plays a significant role in delivering packages. PH operations are identical to a cross-docking system. Numerous studies were conducted to examine solutions in ...
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Impellers are extensively employed across various industrial sectors and in different industrial systems, such as ducted-fan modules. The configuration of ducted-fan modules can be optimized to achieve high impeller p...
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